PS: sorry, the y axis says g(r) but it is the angle probability distribution
Em sexta-feira, 5 de maio de 2023 às 11:24:45 UTC+2, Cecília Álvares escreveu: > (1) indeed I spotted that in some cases they oscilate back and forth > around the target distribution (I am attaching a pic as an example). > However, this is not something that putting a factor < 1 was able to solve. > (2) no, I am working in the NVT ensemble. > (3) my thermostat is working: the temperature is quite well equilibrated > (no weird spikes). The timestep us also small (I am using 5fs atm). > (4) me too :"D > > R: Regarding the implementation in Votca: I saw that link in the paper. So > indeed the interpolation scheme at the onset region that is mentioned in > the paper is not implemented in the basic VOTCA installation and we need to > use those codes in the branch you mentioned, right? > > R: Regarding the bonded potentials: Good idea. That is actually something > I did not try. I test it. > > Photo below: evolution of the angle distribution in a scenario in which I > am optimizing only one potential (i.e., the angle potential) + using a > factor of 0.25 > [image: marvin2.png] > > Em sexta-feira, 5 de maio de 2023 às 09:08:04 UTC+2, Marvin Bernhardt > escreveu: > >> Regarding optimizing non-bonded potentials in crystals, just a list of >> things I would check: >> Are the distributions at the iterations oscillating around the target >> distribution? Or is it rather a slow approach that never gets there? Or is >> it chaotic? >> Are you working at constant pressure? If so, I would try at constant >> volume. >> Is your thermostat working and your time step small enough such that the >> temperature is always as expected in each iteration? >> Well possible, that it just does not work for your system, however, I am >> really surprised, that separating out a single potential in the whole >> system did not work. >> >> Regarding the implementation in Votca: >> It is still in the branch csg/mulit-iie2 at GitHub, you can build it from >> there. It has all the methods from the paper. >> >> Regarding the bonded potentials: >> For this situation it helps to restrict the range such that the >> problematic regions are not included. Votca should then extrapolate bonded >> potentials linearly. >> >> >> On Thursday, 4 May 2023 at 14:46:49 UTC+2 Cecília Álvares wrote: >> >>> Let me just ask one more question if I may: >>> >>> In the section 2.9 of your paper, you talk about how the algorithm is >>> set to create an "alternative RDF" which cherishes an interpolation in the >>> onset region, where the values of the original RDF tend to be very small >>> and the region tend to be poorly sampled (which is a quite good idea btw :) >>> ). In the paper it specifically says range of values that you guys have had >>> good experience with applying this interpolation procedure. In the abstract >>> of the paper it says that the methods are implemented in VOTCA. Do you mean >>> only the specific numerical methods you are using to do the iterative >>> process or do you include also other specific things such as the >>> interpolation protocol you described in section 2.9? >>> >>> I am asking because in my case, sometimes, the distribution coming from >>> the CG simulation ends up having small values that sometimes oscillates a >>> bit back and forward in the onset region but the g(r) has values a bit >>> larger than the value you mentioned in the paper for which the >>> itnerpolation is done (1E-4). This causes weird potentials to happen which >>> could be the reason why everything is going to hell. I am attaching a >>> figure to illustrate the point. Is there a way in which I can change myself >>> the value of the threshold for which I want to apply the interpolation? >>> Maybe in my case I would need to use values higher than 1E-4. It could >>> totally save the day and also make sense: since I am simulating a xtalline >>> material whose superatoms are allowed less movement compared to a liquid, >>> the setup of my interpolation needs to be more strict for the IBI to work. >>> >>> [image: marvin.png] >>> >>> Em quinta-feira, 4 de maio de 2023 às 12:25:09 UTC+2, Cecília Álvares >>> escreveu: >>> >>>> I think at this point I may be ready to just say that indeed IBI cannot >>>> be used to converge to a potential that is able to reproduce the structure >>>> of xtalline materials (or at least the material I am studying). >>>> >>>> I've tried >>>> (1) diminishing the factor used to update the potential (as you >>>> mentioned) and it did not work. >>>> (2) updating literally only one potential at a time in the IBI and >>>> keeping the others literally constant either in the BI potential or in >>>> analytical forms that are able to reproduce perfectly the probability >>>> distributions. This would discard the possibility of dependence on the >>>> degrees of freedom in that sense that the update of one potential is >>>> affecting the distributions related to other potentials. >>>> (3) Although the result is not meant to be bin-size-dependent, I tried >>>> playing with the bin size of both, the references I am feeding to VOTCA, >>>> and of the distributions it is meant to built as the iterative process >>>> runs >>>> for the different potentials. I thought maybe I was not setting up >>>> "proper" >>>> bin sizes for the algorithm. >>>> (4) I tried dividing the angles lying within each of the two peaks in >>>> the initial figure I showed into two different angle types and it also did >>>> not work. >>>> (5) I read your paper and tried to be more careful with issues that you >>>> raised in section 2.9 related to the smoothness of the distributions in >>>> the >>>> onset region (although VOTCA is supposed to take care of this internally >>>> apparently via the extrapolation methodology). Although section 2.10 bring >>>> up issues related to IMC, I also tried some more ideas that came to mind >>>> from reading that section and it didnt work. >>>> (6) I've tried keeping analytical forms for the bonded potentials (I >>>> happen to have analytical forms that perfectly reproduce the >>>> distributions) >>>> and optimize the non-bonded and it also doesnt work. >>>> >>>> Naturaly, in all cases, together with weird distributions, my >>>> potentials are also going to hell as the iterative procedure goes on >>>> (which >>>> explains why the corresponding distributions are weird). >>>> >>>> For sure the problem doesnt have to do with the "sharpness" of the >>>> probability distribution curves (due to the xtalline material being highly >>>> ordered) cause I tried to feed "artificial" target distributions that are >>>> wide and thus less step and I dont converge to anything reasonable either. >>>> >>>> Maybe the shape of the distributions for xtalline materials is not >>>> friendly to be used within IBI to converge to a potential, idk... >>>> Well.. >>>> >>>> Em quarta-feira, 26 de abril de 2023 às 15:19:19 UTC+2, Cecília Álvares >>>> escreveu: >>>> >>>>> (In any case let me try your factor idea, some other stuff that came >>>>> to mind + finish reading your paper so that maybe I have more useful info >>>>> on the problem) >>>>> Em quarta-feira, 26 de abril de 2023 às 14:05:06 UTC+2, Cecília >>>>> Álvares escreveu: >>>>> >>>>>> Indeed, this could be the reason why I have this weird non-smoothness >>>>>> in the plots I sent in my 2nd message (the ones concerning a less >>>>>> coarsened >>>>>> mapping), because indeed in this case I was optimizing all the three >>>>>> bonded >>>>>> potentials at once. I will try not doing them at the same time and see >>>>>> if >>>>>> the smoothness-issue improves. >>>>>> >>>>>> But then this would not explain the issues I had in the original post >>>>>> I made, which concerned another mapping (a highly coarsened one). If the >>>>>> problem was a matter of optimizing more than one bonded potential at >>>>>> once, >>>>>> I should have had good results when I tried to do IBI only for one angle >>>>>> type and kept the potential for bonds constant (at a BI guess) >>>>>> throughout >>>>>> the procedure. But unfortunately my angle distribution still converges >>>>>> to >>>>>> something ultra weird with 3 peaks. >>>>>> >>>>>> PS: maybe my last message was too big and maybe it was confusing, but >>>>>> the figures I sent in my 1st message and in my 2nd message are for >>>>>> different mappings. In the first one (let's call it mapping A), I have >>>>>> only >>>>>> 1 bond type and 1 angle type. For this one I did try optimizing >>>>>> separately >>>>>> to see if it would fix the problem and yet I reached weird results. The >>>>>> second message had figures of a less coarsened mapping (let's call it >>>>>> mapping B) in which I somewhat successfully converge to potentials that >>>>>> yield more or less rightful distributions (apart from the smoothness >>>>>> issue). I only brought up the results of the second mapping to show that >>>>>> the same strategy "worked" for deriving bonded potentials via IBI for >>>>>> another mapping. Sorry if I made it more confusing! >>>>>> >>>>>> Em quarta-feira, 26 de abril de 2023 às 08:29:58 UTC+2, Marvin >>>>>> Bernhardt escreveu: >>>>>> >>>>>>> Hey Cecília, >>>>>>> >>>>>>> Oh ok, then it is probably not the interaction with the non-bonded >>>>>>> terms, that causes issues. But I believe something similar is going on, >>>>>>> that indeed has something to do with your system being a solid/crystal: >>>>>>> IBI is a very good potential update scheme, when the degrees of >>>>>>> freedom are well separated. For molecules in liquids, angles and bonds >>>>>>> are >>>>>>> usually well separated, i.e. changing the potential of one, does not >>>>>>> affect >>>>>>> the dist of the other much. But multiple occurrences of equivalent DoFs >>>>>>> also need to be well separated for IBI to work well. In your case, >>>>>>> consider >>>>>>> a single angle potential between three beads in the crystal is changed, >>>>>>> but >>>>>>> all the others are kept constant. It will change the distribution of >>>>>>> that >>>>>>> angle, but also have effect on different angles. In that case IBI is >>>>>>> not >>>>>>> providing a good potential update at each iteration. >>>>>>> What is happening in detail, I believe, is that the angle potential >>>>>>> of all angles is updated by IBI, but this leads to an “overshoot”. The >>>>>>> next >>>>>>> iteration, IBI tries to compensate, but overshoots again in the other >>>>>>> direction. You can easily test if this is what is happening, plotting >>>>>>> even >>>>>>> and uneven iterations separately, i.e. compare a plot at iterations 10, >>>>>>> 12, >>>>>>> 14 with 11, 13, 15. >>>>>>> This has happened to me before with ring molecules, where the >>>>>>> situation is similar. A possible solution is to scale the update, by >>>>>>> some >>>>>>> factor between 0 and 1 (I'd try 0.25). >>>>>>> >>>>>>> Also test this for the bond potential, I guess this is happening >>>>>>> there too, otherwise it should converge within ~20 iterations. >>>>>>> >>>>>>> Greetings, >>>>>>> Marvin >>>>>>> On Tuesday, 25 April 2023 at 10:25:59 UTC+2 Cecília Álvares wrote: >>>>>>> >>>>>>>> Hey Marvin, >>>>>>>> >>>>>>>> Thanks a lot for the reply! >>>>>>>> I will have a look on the paper right now and do some thinking. In >>>>>>>> fact, I wanted to test the possibility of optimizing the bonded >>>>>>>> potentials >>>>>>>> first and, after its optimization is done, optimize the non-bonded. So >>>>>>>> basically there is no optimization of non-bonded whatsover being done >>>>>>>> in my >>>>>>>> simulation. To build the target distributions, I sampled an atomistic >>>>>>>> system in which the non-bonded forces were artificially removed. After >>>>>>>> having a trajectory file of this AA system, I built the corresponding >>>>>>>> target distributions to be used in VOTCA with csg_stat. For what is >>>>>>>> worth >>>>>>>> it, the target distributions of angle and bond don't seem at all weird >>>>>>>> relative to the "real ones", of when non-bonded forces exist. And >>>>>>>> then, >>>>>>>> after having the target distributions, I set up the CG MD simulations >>>>>>>> within the IBI to have only bonded potential also. So, besides there >>>>>>>> being >>>>>>>> no non-bonded potential optimization, there is also no non-bonded >>>>>>>> forces at >>>>>>>> all in my CG system. But I dont think this should be a problem, right? >>>>>>>> It >>>>>>>> makes sense to entrust the CG bonded potentials to reproduce the >>>>>>>> target >>>>>>>> distributions of the AA bonded potentials. >>>>>>>> >>>>>>>> What I did try also, and that is in allignment with your idea, was >>>>>>>> to set up two IBI runs: (1) one run to optimize *only* the >>>>>>>> potential for the bonds and keep the angle potential active (in this >>>>>>>> case >>>>>>>> the latter comes from a simple BI) and (2) one run to optimize only >>>>>>>> the >>>>>>>> potential for the angles and keep the bond potential active (in this >>>>>>>> case >>>>>>>> the latter comes from a simple BI). In the case (1) it seems that I >>>>>>>> converge to a potential for bonds that is quite able to reproduce the >>>>>>>> corresponding distribution, while in the case (2) I converge more and >>>>>>>> more >>>>>>>> to potentials that give super weird distributions (like with three >>>>>>>> weird >>>>>>>> peaks, as I showed in the figure above) >>>>>>>> >>>>>>>> Concerning the phase of the system: it is a solid system. More >>>>>>>> specifically, it is a coarsened grained version of ZIF8 in which the >>>>>>>> whole >>>>>>>> repeating unit was assumed to be one bead. I know that IBI has not at >>>>>>>> all >>>>>>>> been developed for solids and even further not for MOFs - the goal is >>>>>>>> actually to derive potentials in the CG level using many different >>>>>>>> strategies (IBI, FM, relative entropy) and evaluate the results. In >>>>>>>> any >>>>>>>> case, I dont think that the fact that my system is a xtalline solid >>>>>>>> could >>>>>>>> be the reason why my results are super weird (right?). It seems like >>>>>>>> such a >>>>>>>> simple system when in the CG level. >>>>>>>> >>>>>>>> For what is worth it, I am also assessing different mappings. >>>>>>>> Following the same strategy of optimizing first bonded-potential for a >>>>>>>> less >>>>>>>> coarsened mapping (2 beads), I am able to reach less weird results. >>>>>>>> For >>>>>>>> example, you can find below the evolution of the corresponding >>>>>>>> distributions as I perform more iterations for this system (it has one >>>>>>>> bond >>>>>>>> type and two angle types). I think there is still a problem since we >>>>>>>> can >>>>>>>> see some tendency of the distributions becoming non-smooth as I do >>>>>>>> more >>>>>>>> iterations, but the results are definitely less weird. >>>>>>>> >>>>>>>> [image: picture.png] >>>>>>>> >>>>>>>> Em segunda-feira, 24 de abril de 2023 às 20:50:14 UTC+2, Marvin >>>>>>>> Bernhardt escreveu: >>>>>>>> >>>>>>>>> Hi Cecília, >>>>>>>>> >>>>>>>>> I once encountered similar problems with bonded and non-bonded >>>>>>>>> interactions. See Fig. 9 of this paper >>>>>>>>> <https://pubs.acs.org/doi/10.1021/acs.jctc.2c00665>. In short: >>>>>>>>> The problem was that the potential update of the non-bonded has some >>>>>>>>> influence on the bonded distribution, and vice versa. But the >>>>>>>>> potential >>>>>>>>> update is calculated as if they were independent. >>>>>>>>> >>>>>>>>> The fix in my case was to update the two interactions alternately >>>>>>>>> using `<do_potential>1 0</do_potential>` for bonded and `< >>>>>>>>> do_potential>0 1</do_potential>` for non-bonded interactions. You >>>>>>>>> could try something similar. >>>>>>>>> >>>>>>>>> Otherwise, is your system liquid? Are there non-bonded >>>>>>>>> interactions that you are optimizing at the same time? >>>>>>>>> >>>>>>>>> Greetings, >>>>>>>>> Marvin >>>>>>>>> >>>>>>>>> On Monday, 24 April 2023 at 16:56:42 UTC+2 Cecília Álvares wrote: >>>>>>>>> >>>>>>>>>> Hey there, >>>>>>>>>> >>>>>>>>>> I am currently trying to derive bonded potentials of a very >>>>>>>>>> simple CG system (containing only one bond type and one angle type) >>>>>>>>>> using >>>>>>>>>> IBI. However, I have been failing miserably at doing it: instead of >>>>>>>>>> reaching potentials that are better and better at reproducing the >>>>>>>>>> target >>>>>>>>>> distributions for the bond and for the angle, I end up having weider >>>>>>>>>> and >>>>>>>>>> weider distributions as I do the iterations. I am posting a plot of >>>>>>>>>> the >>>>>>>>>> bond and angle distributions to give a glimpse on the "weirdness". I >>>>>>>>>> have >>>>>>>>>> already tried: >>>>>>>>>> (1) providing very refined (small bin size and a lot of bins) >>>>>>>>>> target distributions of excelent quality (meaning not noisy at all) >>>>>>>>>> for the >>>>>>>>>> bond and the angle. Similarly, I have also tried using less refined >>>>>>>>>> target >>>>>>>>>> distributions (larger bin sizes and less amount of bins). >>>>>>>>>> (2) varied a lot the setup in the settings.xml concerning bin >>>>>>>>>> sizes for the distributions to be built at each iteration from the >>>>>>>>>> trajectory file. I have tried very small bin sizes as well as large >>>>>>>>>> bin >>>>>>>>>> sizes. >>>>>>>>>> (3) increasing the size of my simulation box hoping that maybe it >>>>>>>>>> was all a problem of not having "enough statistics" to build good >>>>>>>>>> distributions at each iteration within the trajectory file I was >>>>>>>>>> collecting >>>>>>>>>> from my simulations. >>>>>>>>>> >>>>>>>>>> None of these things has worked and I think I ran out of ideas of >>>>>>>>>> what could possibly be the cause of the problem. Does anyone have >>>>>>>>>> any >>>>>>>>>> insights? >>>>>>>>>> >>>>>>>>>> I am also attaching my target distributions (this is the scenario >>>>>>>>>> in which I am feeding target distributions lot of points and smaller >>>>>>>>>> bin >>>>>>>>>> size) and the settings.xml file for what is worth it. >>>>>>>>>> >>>>>>>>>> [image: plots.png] >>>>>>>>>> >>>>>>>>> -- Join us on Slack: https://join.slack.com/t/votca/signup --- You received this message because you are subscribed to the Google Groups "votca" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/votca/f7f292c5-a0d1-477d-8248-8d81ebf3a582n%40googlegroups.com.
